tbuckley/cabot-search huggingface dataset:
Evaluating an AI-based nutrition expert platform delivered via SMS-text to support patients with cancer.
Authors: Marissa Lubin Buchan, Hao Tang, Susan Bratton, Sridevi Padmanabhan, David Raben
Journal: Journal of Clinical Oncology (2022)

1569 Background: Interventions incorporating nutritional strategies can prevent and manage nutrition-related symptoms, however, due to a shortage of oncology dietitians (RD CSO) combined with healthcare access disparities, many patients do not receive the support they need, resulting in poor outcomes and quality of life (QoL). High rates of cell phone utilization among all demographics offers a unique opportunity to provide interventions using mobile technology. Methods: Launched to select groups in 2019, Ina (trademarked by Savor Health LLC) is a virtual nutrition assistant powered by an artificial intelligence (AI)-enabled expert platform, to facilitate self-management of cancer treatment side effects. The platform combines evidence, expertise, and unique patient data to deliver the personalized guidance patients would receive from an RD CSO, “on-demand” via text. This study applied the RE-AIM framework to evaluate the intervention from five dimensions. Results: Reach: The program reached 1,706 users as of 2021. Based on self-report among 1209 users, 78% are patients, 18% are caregivers, and 5% are healthcare professionals with 66% female and 34% male. Ina supports all cancer types, and top diagnoses among users are genitourinary (28%), lung (20%), gynecologic (16%), gastrointestinal (15%), and breast (11%). Disease burden is high, with 62% of users reporting they are experiencing nutrition-addressable symptoms at any given time. Effectiveness: Based on weekly patient reported outcome (PRO) surveys, 87% of respondents report Ina helps them manage symptoms, and 80% report that using Ina has improved their QoL. The cumulative likelihood to recommend is 4.1 on a 5-point scale. Adoption: Users are from over 18 cancer organizations, proving the feasibility and accessibility of this intervention. Implementation: Ina is accessible 24/7 via text, and is offered to patients in a B2B2C model. Users typically receive responses to nutrition-related questions within seconds from the AI platform (or 1-3 minutes with live RD oversight). Each active user (one that engages at least once in a given month) asks an average of 2.8 questions per month. Maintenance: The median time users remain on the platform is 156 days (range 0-884) and 57% of evaluable users stayed on the platform 6 months or longer. The platform’s database, which includes over 54,000 referenced interventions, grows daily via supervised machine learning supported by RD CSOs. When surveyed on future feature development, respondents are most interested in tele-nutrition (57%), mental health (65%), and stress management (62%). Conclusions: Initial data suggests this is a feasible and accessible tool to support cancer patients’ unique nutrition and symptom-management needs. Clinical trials are needed to validate feasibility and assess impact on clinical and QoL outcomes. Product development to integrate language and cultural preferences is ongoing.
Neoadjuvant sintilimab combined with chemotherapy in patients with resectable esophageal squamous cell carcinoma (ESCC): Preliminary results from a phase II study.
Authors: Jincheng Guo, Chengrui Qiao, Jiabin Lu, Shiqing Yang, Boyi Zhang
Journal: Journal of Clinical Oncology (2022)

e16008 Background: Although preoperative chemoradiotherapy is the standard of care for patients with resectable locally advanced esophageal cancer, prognosis still remains poor. Combining PD-1 blockade to chemotherapy has demonstrated significant clinical benefits in first line treatment of metastatic ESCC. Sintilimab, a fully human IgG4 monoclonal antibody that binds to programmed cell death receptor-1 (PD-1), has shown remarkable clinical efficacy in metastatic ESCC. We aimed to assess the activity and safety profile of the combination of sintilimab with paclitaxel and cisplatin for neoadjuvant treatment of ESCC. Methods: In this ongoing, single-arm, phase II study, we recruited patients from the First Affiliated Hospital of Henan University of Technology in China with histopathologically diagnosed resectable ESCC who had clinical cT2-4/N1-3M0 (stage II-IVA). Patients were given 2 cycles of chemotherapy (nab-paclitaxel 260 mg/m 2 , d1 and cisplatin 75 mg/m 2 , d1-3) in combination with 2 cycles of sintilimab (200mg, iv, d1, q3w), followed by esophagectomy. The primary endpoint was pathological complete response (pCR). The secondary endpoints included major pathological remission (MPR) and objective response rate (ORR). Results: Between Nov 2020 and Dec 2021, 15 patients were enrolled and commenced treatment. A total of 11 patients (75%) completed neoadjuvant and radical resection, 4 patients refused surgery. Six patients (54.5%) achieved major pathologic response (MPR), including five (45.5%) with a pathologic complete response (pCR) in primary tumor. According to RECIST v1.1, 1 of 8 patients (12.5%) achieved partial response (CR), 4 of 8 patients (50%) achieved partial response, and 3 of 8 patients (37.5%) achieved stable disease (SD). The objective response rate (ORR) and disease control rate (DCR) for 8 patients were 62.5% and 100%, respectively. The most frequent treatment-related adverse events (TRAE) included leukopenia (60%), nausea (40%) and diarrhea (20%). The grade 3 or 4 TRAE were leukopenia (26.7%), neutropenia (20%) and pneumonia (6.7%). There was no surgical delays or unexpected surgical complications related to drug toxicity. Conclusions: Neoadjuvant combination of sintilimab and chemotherapy is a safe and efficacious treatment option for patients with resectable ESCC, and 45.5% pCR rate is encouraging. Our clinical study is still enrolling, and the survival effects are under follow up. Clinical trial information: ChiCTR2000040345.
Breakthrough COVID-19 cases and hospitalization risk: ASCO COVID-19 registry.
Authors: Suanna Steeby Bruinooge, Dax Kurbegov, Melinda Kaltenbaugh, Jen Hanley Hanley Williams, Julie R. Gralow, Elizabeth Garrett-Mayer
Journal: Journal of Clinical Oncology (2022)

e18807 Background: The ASCO Registry was created to analyze the impact of COVID-19 (COVID) on treatment (Tx) and outcomes of patients (pts) with cancer. Vaccination questions were added in 2021, enabling examination of breakthrough cases  i.e., SARS-CoV-2 infection after vaccination. Methods: The Registry includes pts who test positive for SARS-CoV-2 and have clinically evident cancer receiving Tx or resected cancer on adjuvant Tx &lt;12 months since surgery at the time of the positive test. Practices report data on COVID vaccine type and dates, positive SARS-CoV-2 test date, and subsequent Tx. Breakthrough cases were defined as 1) &gt; 35 days after 1 st Pfizer dose, 2) &gt; 42 days after 1 st Moderna dose, 3) &gt; 14 days after 1 st Janssen dose, or 4) &gt; 42 days after 1 st unknown vaccine dose. Data submission cutoff for all practices was February 2, 2022. Summary statistics and exact binomial 95% confidence intervals (CIs) were calculated. Results: This analysis reports on 231 pts with breakthrough cases. Median age is 68 years and 57% of pts are over age 65. Of 73 pts with non-metastatic solid tumors, 19% were hospitalized. Of 74 with metastatic solid tumors, 39% were hospitalized. Of 75 with B-cell malignancies, 32% were hospitalized. Of 9 with other hematologic malignancies, 56% were hospitalized. While the fraction of patients in the ASCO registry with breakthrough cases who were hospitalized remained fairly constant throughout 2021 (approximately 40%), those with breakthrough cases occurring in the last month of 2021 and early 2022 had a lower hospitalization rate (approximately 20%), which is consistent with less severe cases of COVID-19 in patients infected with the omicron variant (the predominant variant in the US in Dec 2021- Jan 2022) (Table). The majority of breakthrough cases occurred more than 6 months after initial vaccination (71%) and the median time to breakthrough infection from initial vaccination was 7.3 months (IQR: 5.6  9.9). The Registry continues to accrue cases and additional vaccine data; analysis will be updated with most current vaccination data for possible Annual Meeting presentation. Conclusions: Hospitalizations among patients with cancer and breakthrough COVID in the ASCO Registry occur at a high rate, particularly among patients with advanced cancers and hematologic malignancies. This decrease in recent months is likely due to increased incidence of the Omicron variant that resulted in milder COVID symptoms among those infected. A majority of SARS-CoV-2 infections occurring six months or more after vaccination suggests waning vaccine efficacy over time that could be impacted by additional doses.[Table: see text]
Staging locally advanced cervical cancer with FIGO 2018 versus FIGO 2008: Impact on overall survival and progression-free survival in the OUTBACK trial (ANZGOG 0902, RTOG 1174, NRG 0274).
Authors: Linda R. Mileshkin, Kathleen N. Moore, Elizabeth H Barnes, Yeh Chen Lee, Val Gebski, Kailash Narayan, Nathan Bradshaw, Katrina Diamante, Anthony W. Fyles, William Small, David K. Gaffney, Pearly Khaw, Susan Brooks, J Spencer Thompson, Warner King Huh, Matthew Carlson, Katina Robison, Danny Rischin, Martin R. Stockler, Bradley J. Monk
Journal: Journal of Clinical Oncology (2022)

5531 Background: The International Federation of Obstetrics and Gynecology staging system for cervical cancer (FIGO 2008) was revised in 2018 to incorporate lymph node involvement (FIGO 2018). OUTBACK is an international, randomized phase 3 trial of adjuvant chemotherapy versus observation after standard of care treatment with chemoradiation for women with locally advanced cervical cancer. OUTBACK found no benefit from the addition of adjuvant chemotherapy. We evaluated the effects of classifying participants with these 2 staging systems in the OUTBACK trial population. Methods: OUTBACK recruited April 2011 to June 2017 and staged participants according to FIGO 2008. Lymph node status, smoking status, age, race and histological subtype were documented at trial entry as important prognostic factors. We assessed the effects of stage grouping into stage I, II, and III/IVa with FIGO 2008 versus FIGO 2018, on progression-free survival (PFS) and overall survival (OS) at 5 years using Kaplan-Meier estimates, and in univariable proportional-hazards regression analyses, and in multivariable analyses adjusting for important prognostic factors and randomly allocated treatment. Results: All 919 study participants had complete data for staging according to the 2 staging systems and most prognostic factors for adjustment. Among all participants, the 5-year outcomes were PFS = 62% and OS = 72%. Classification according to FIGO 2018 rather than FIGO 2008 yielded higher 5-year PFS and OS in each stage group (see table for numbers of participants, PFS and OS for each stage group). Predictors of PFS in multivariable analysis included squamous vs non-squamous histology (HR 0.71 for FIGO 2008 and 0.74 for FIGO 2018), but not nodal involvement when FIGO 2018 was used. Both staging systems were the only independently significant prognostic factors in both univariable and multivariable analyses (all p &lt; 0.0001) for both PFS and OS. Conclusions: Compared to FIGO 2008, reclassifying pts by FIGO 2018 staging resulted in more pts being classified as stage 3 due to the incorporation of nodal status. Staging locally advanced cervical cancer using FIGO 2018 rather than FIGO 2008 resulted in higher PFS and OS in each stage grouping that reflected stage migration, not a true improvement in outcomes. FIGO stage remains the strongest predictor of overall survival after CRT but survival outcomes by stage in trials using the old vs new staging system are not comparable. Clinical trial information: ACTRN12610000732088. [Table: see text]
A circulating miRNA-based AI prediction system to identify multiple types of cancer.
Authors: Chih-Hsun Wu, Ming-Jing Hwang, Chia-Ming Chang
Journal: Journal of Clinical Oncology (2022)

3050 Background: Cancer is a major problem for human health. Development of an early diagnostic tool can increase the survival of cancer patients. Liquid biopsies have many advantages over traditional tumor tissue biopsies. Circulating microRNAs (miRNAs) are one type of liquid biopsies in part because they regulate the expression and thus functions of their target genes. Circulating miRNAs are stable, non-invasive and changes in their expression are detectable in the early stage of cancer progression, often before clear evidence of tissue biopsy/image tests. To date, there are few liquid biopsy-based tools for multiple-cancer diagnosis and their performance is unsatisfactory. The development of a non-invasive, effective early detection system for cancers is urgently needed. Methods: We integrated and investigated circulating miRNA expression data of 5046 non-cancer samples along with 3856 cancer samples of 6 major cancer types downloaded from publicly available databases. We used these expression data along with gender to establish a multiple cancer type AI prediction system. Furthermore, we built comprehensive interaction networks (miRNA-drug, miRNA-target gene) and performed functional enrichment analysis. Results: We constructed high-performance AI prediction model that can detect and differentiate 6 cancer groups from one non-cancer group. A median of sensitivity of 93.84% in test data was achieved for the multiple cancer classification task. A panel of gender and 15 most important circulating miRNAs was further shown to achieve excellent performance (sensitivity = 90.44%), with just a bit of decrease in the sensitivity of using the full set (gender and 2565 miRNAs). The 15 key circulating miRNAs worked well for the early stage (stage 1: sensitivity = 88%), much better than other liquid-biopsy results reported in the literature. This is important because these miRNAs and the AI system can be used to significantly decrease clinical cost and increase efficiency of early diagnosis, not to mention it is non-invasive. Finally, we constructed comprehensive interaction networks (drug/ target gene) for these key miRNAs to explore potential therapeutic strategies and understand the underlying biological mechanisms. Conclusions: In the study, we constructed the multiple-cancer prediction AI system to classify groups of normal individuals and cancer patients of multiple types, while finding key circulating miRNAs. As several key circulating miRNAs were shown to be potential drug targets or serve as diagnosis biomarkers to fulfill the aim of cancer precision medicine, this work represents a significant step toward achieving the goal of developing a non-invasive tool for early diagnosis of cancers.
Insurance-based disparities in Waldenstrom Macroglobulinemia: An NCDB analysis.
Authors: Karan Chohan, Jithma P. Abeykoon, Stephen M. Ansell, Morie A. Gertz, Prashant Kapoor, Aneel Paulus, Sikander Ailawadhi, Craig B. Reeder, Thomas E. Witzig, Thomas Matthew Habermann, Martha Lacy, Robert A. Kyle, Ronald S. Go, Jonas Paludo
Journal: Journal of Clinical Oncology (2022)

e19562 Background: Considerable healthcare resource utilization and financial burden have been associated with the treatment of Waldenstrom Macroglobulinemia (WM); however, the impact of health insurance status on patient outcomes has not been explored. We aimed to assess the insurance-based outcome relationship in WM using the National Cancer Database (NCDB). Methods: We analyzed patient-level data obtained from the NCDB, a database representing more than 70% of newly diagnosed cancer cases nationwide. All newly diagnosed WM cases (n = 8540) between 2004 to 2017 were identified. Only patients who underwent treatment were included. Insurance status was recorded by assessing the primary payer at the time of diagnosis. Due to Medicare eligibility criteria, age-based (&lt; 65 and ≥65 years) stratified analysis was conducted. Cox proportional hazards model was utilized to analyze survival. Time-to-event analysis was conducted based on date-of-diagnosis using the Kaplan-Meier method and log-rank test. Results: Analysis was conducted on 3878 patients after meeting inclusion criteria, with a median follow-up time of 54.6 months. Among patients &lt; 65 years (n = 1249; median age: 58 years; male: 62.4%), those with non-private insurance had inferior survival on multivariate analysis (Table) after adjusting for patient demographics, comorbidities, income, education, treatment center characteristics, and treatment start time. Significant overall survival (OS) differences were seen in those &lt; 65 years (log-rank p &lt; 0.001), with 5-year OS highest among patients with private insurance 91.2%, compared to Medicaid 79.8%, uninsured 77.4%, and Medicare 70.2%. In patients &lt; 65 years, compared to private insurance, uninsured patients were more likely to be of Black race, reside in lower income areas, and be treated at non-academic centers (all p &lt; 0.05). Both Medicaid and Medicare patients &lt; 65 years were more likely to have a higher Charlson-Deyo comorbidity index (&gt; 1) and live in areas of lower educational attainment and household income compared to private insurance (all p &lt; 0.05). In patients ≥65 years (n = 2629; median age: 75 years; 60.6% males), no insurance-based OS (log-rank p = 0.096) differences were seen. Conclusions: Based on our study, significant insurance-based disparities exist in WM, where patients &lt; 65 years old who are uninsured, or non-privately insured are at a higher risk of mortality. While the root cause of these differences is not fully elucidated, efforts should focus on ensuring that all patients have equal access to care regardless of primary payer status.[Table: see text]
Better tumor immune microenvironment in patients with older lung adenocarcinoma.
Authors: Yongjie Wang, Ronghua Yang, Dong Wang, Yunpeng Xuan, Yi Yu, Yingxue Qi, Minghui Ge, Ningning Luo, Xiaofeng Zhu, Mengmeng Li
Journal: Journal of Clinical Oncology (2022)

e20544 Background: Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Immunotherapies (ICIs) have been confirmed to improve the clinical outcomes of LUAD patients. Efficacies of ICIs are considered strongly associated with tumor immune microenvironments (TIME). Age-related immune dysfunction might induce difference on the efficacy of ICIs between younger and older patients. However, the potential effect of age on TIME remains little known and controversial. Herein, we aimed to analysis the association between age and TIME based on The Cancer Genome Atlas (TCGA) database. Methods: We screened out 582 LUAD patients with complete information, whose tumors underwent next-generation sequencing (NGS) detection in TCGA. All patients were divided into two groups according to age, the younger group (age &lt; 50-year old) and the older group (age≥50-year old). The differences of immune-related signatures between the two groups were calculated according to previous reports. We also analyzed the differences in immune-related signature between different clinical stages. P-values were calculated via the T.Test. Results: In total 582 patients with LUAD in our study, 115 (19.76%) patients in younger group and 467 (80.24%) patients in older group were found. Many immune-related signatures were found significantly higher in older group than in younger group, including cytolytic activity (CYT) (p = 0.0352), expanded immune signature (p = 0.0065), T cell inflamed gene expression profile (GEP) (p = 0.0048), IFN-γ-related response genes (p = 0.0346), immune signature (p = 0.0022), immunosuppression (p = 0.0065), major histocompatibility complex class I (MHC class I) (p = 0.0319), T-cell survival (p = 0.0235), tertiary lymphoid structures (TLS) signature (p = 0.0001) and total_TILs_scores (p = 0.0020). In addition, tertiary lymphoid structure (p = 0.0355) and TLS_signature (p = 0.0243) were found significantly difference in different clinical staging, which decreased as the staging get later. On the contrary, cell cycle score (p = 0.0001) increased as the staging get later. Conclusions: Our study evaluated the impact of age and clinical stage on the TIME in patients with LUAD using a threshold of 50 years old for the first time. We founded that LUAD patients in older group had better TIME than in younger group and some immune-related signatures were significantly related with clinical staging.
Platelet derived growth factor receptor alpha (<i>PDGFRA</i>) mutant gastrointestinal stromal tumours (GISTs): Clinicopathological characteristics and outcomes from a regional centre in the United Kingdom.
Authors: David M Favara, Han Hsi Wong, Jennifer Harrington, Olivier Giger, Venkata Ramesh Bulusu
Journal: Journal of Clinical Oncology (2022)

11534 Background: GISTs are the most common mesenchymal tumours of the gastrointestinal tract with an annual incidence of 10-15 per million. 10% of GISTS have activating mutations in the PDGFRA gene. We report our 13 year experience of all the PDGFRA-mutated GISTs in our regional centre in Cambridge. Methods: PDGFRA-mutant GISTs were identified from the Cambridge GIST database. Demographics, clinical and histopathological features, survival and response to tyrosine kinase inhibitors of all the patients from 2008-2021 were reviewed. Results: n = 50 (male:female 1.5:1) Median age 68 years (range 19-87). 8% of patients were under the age of 40 years. Tumour size ranged from 1-26 cm with a median of 5 cm. Mitotic index ranged from 1-51 with a median of 1 mitosis/5mm2. 52% of GISTs were located in the gastric body. Histological subtypes: 44% epithelioid, 36% mixed and 20% spindle cell. 38% of cases had high KIT expression (immunohistochemistry), whilst 48% had patchy expression and 14% were negative. Most were DOG1-positive (94%). 76% had radical surgery, 60% had laparoscopic resection. 24% were assessed as being high risk GISTs using the modified AFIP model contrasted to 13% being high risk with prognostic contour mapping. 13% developed metastatic disease with liver being the most common metastatic site. The table shows PDGFRA mutational analysis results: 58% had a D842V mutation. None had a KIT mutation. With a median follow up of 55.1 months, 82% were alive. 6 patients died from metastatic GIST and 3 from other causes. Median time to metastatic disease in resected GISTs was 30.1 months and median time from metastatic diagnosis to death was 18.5 months. Patients who presented with metastatic disease had poor survival compared with patients with localised disease ( p=0.001). 8 patients were treated with tyrosine kinase inhibitors including imatinib, sunitinib and regorafenib prior to 2020 with no objective responses. 3 patients were treated with Avapritinib since 2020 within the compassionate use programme. All 3 patients had partial responses and 2 patients are continuing Avapritinib with no grade 3 adverse events. Conclusions: We report the largest single centre PDGFRA-mutant GIST cohort from Europe. Male preponderance and exclusive gastric location were observed. KIT expression was patchy to negative in the majority of patients. 58% had PDGFRA D842V mutations for which Avapritinib has been recently approved. No objective responses were seen with imatinib, sunitinib or regorafenib. Our early experience with Avapritinib is promising.[Table: see text]